Fast Probability Generating Function Method for Stochastic Chemical Reaction Networks
Cited 0 times inCited 0 times in
- Fast Probability Generating Function Method for Stochastic Chemical Reaction Networks
- Kim, Pilwon; Lee, Chang Hyeong
- SIMULATION; KINETICS; SYSTEMS
- Issue Date
- UNIV KRAGUJEVAC
- MATCH-COMMUNICATIONS IN MATHEMATICAL AND IN COMPUTER CHEMISTRY, v.71, no.1, pp.57 - 69
- Chemical master equations of the stochastic reaction network can be reformulated into a partial differential equation(PDE) of a probability generating function (PGF). Such PDEs are mostly hard to deal with due to variable coefficients and lack of proper boundary conditions. In this paper, we propose a way to reduce PGF-PDEs into a sparse linear system of coefficients of a power series solution. A power of such matrix gives a fast approximation of the solution. The process can be further accelerated by truncating high-order moments. The truncation also makes the method applicable to reaction networks with time-varying reaction rates. We show numerical accuracy of the method by simulating motivating biochemical examples including a viral infection model and G(2)/M model.
- ; Go to Link
- Appears in Collections:
- SNS_Journal Papers
- Files in This Item:
can give you direct access to the published full text of this article. (UNISTARs only)
Show full item record
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.